Parametric randomization-based methods for correcting for treatment changes in the assessment of the causal effect of treatment.

Abstract:

:We develop parametric maximum likelihood methods to adjust for treatment changes during follow-up in order to assess the causal effect of treatment in clinical trials with time-to-event outcomes. The accelerated failure time model of Robins and Tsiatis relates each observed event time to the underlying event time that would have been observed if the control treatment had been given throughout the trial. We introduce a bivariate parametric frailty model for time to treatment change and time to trial endpoint. Estimating equations which respect the randomization are constructed and compared to maximum likelihood methods in a simulation study. The Concorde trial of immediate versus deferred zidovudine in HIV infection is used as a motivating example and illustration of the methods.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Walker AS,White IR,Babiker AG

doi

10.1002/sim.1618

subject

Has Abstract

pub_date

2004-02-28 00:00:00

pages

571-90

issue

4

eissn

0277-6715

issn

1097-0258

journal_volume

23

pub_type

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